Quantitative Classification Model of Composite Product Image Based on Event-Related Potential
As an important research tool in neuroscience, event-related potential (ERP) technology enables in-depth analysis of the consumer’s product image cognition process and complements and verifies the product image cognition model at the ERP level. It provides an important theoretical basis for systemat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-07-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/13/7972 |
| _version_ | 1797592099860774912 |
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| author | Yan Li Huan Li Wu Song Chen Le |
| author_facet | Yan Li Huan Li Wu Song Chen Le |
| author_sort | Yan Li |
| collection | DOAJ |
| description | As an important research tool in neuroscience, event-related potential (ERP) technology enables in-depth analysis of the consumer’s product image cognition process and complements and verifies the product image cognition model at the ERP level. It provides an important theoretical basis for systematically capturing product image and improvement of the product image cognitive model. In this work, the correlation between ERP data, product image word pairs and the degree of semantic match with the product is investigated, and a support vector machine algorithm is selected to build a classification model with physiological data (behavioral data + ERP data) as the independent variable and the degree of semantic match with the product image as the dependent variable. By adjusting the model parameters, the final classification accuracy reaches 95.667%, which shows that the model has some reliability and is a viable research method for ERP-based product image researchers in the future. |
| first_indexed | 2024-03-11T01:46:37Z |
| format | Article |
| id | doaj.art-eba131b081764b4b9af66cab42be3448 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T01:46:37Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-eba131b081764b4b9af66cab42be34482023-11-18T16:14:05ZengMDPI AGApplied Sciences2076-34172023-07-011313797210.3390/app13137972Quantitative Classification Model of Composite Product Image Based on Event-Related PotentialYan Li0Huan Li1Wu Song2Chen Le3College of Mechatronic and Automation, Huaqiao University, Xiamen 361021, ChinaCollege of Mechatronic and Automation, Huaqiao University, Xiamen 361021, ChinaCollege of Mechatronic and Automation, Huaqiao University, Xiamen 361021, ChinaCollege of Mechatronic and Automation, Huaqiao University, Xiamen 361021, ChinaAs an important research tool in neuroscience, event-related potential (ERP) technology enables in-depth analysis of the consumer’s product image cognition process and complements and verifies the product image cognition model at the ERP level. It provides an important theoretical basis for systematically capturing product image and improvement of the product image cognitive model. In this work, the correlation between ERP data, product image word pairs and the degree of semantic match with the product is investigated, and a support vector machine algorithm is selected to build a classification model with physiological data (behavioral data + ERP data) as the independent variable and the degree of semantic match with the product image as the dependent variable. By adjusting the model parameters, the final classification accuracy reaches 95.667%, which shows that the model has some reliability and is a viable research method for ERP-based product image researchers in the future.https://www.mdpi.com/2076-3417/13/13/7972product imagesemantic matchingcognitive processingERPhuman factors engineering |
| spellingShingle | Yan Li Huan Li Wu Song Chen Le Quantitative Classification Model of Composite Product Image Based on Event-Related Potential Applied Sciences product image semantic matching cognitive processing ERP human factors engineering |
| title | Quantitative Classification Model of Composite Product Image Based on Event-Related Potential |
| title_full | Quantitative Classification Model of Composite Product Image Based on Event-Related Potential |
| title_fullStr | Quantitative Classification Model of Composite Product Image Based on Event-Related Potential |
| title_full_unstemmed | Quantitative Classification Model of Composite Product Image Based on Event-Related Potential |
| title_short | Quantitative Classification Model of Composite Product Image Based on Event-Related Potential |
| title_sort | quantitative classification model of composite product image based on event related potential |
| topic | product image semantic matching cognitive processing ERP human factors engineering |
| url | https://www.mdpi.com/2076-3417/13/13/7972 |
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